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Activity Number:
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240
- Computationally Intensive Methods for Estimation and Inference
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Type:
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Contributed
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Date/Time:
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Monday, July 31, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #324257
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Title:
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A Missing Technique for Estimating Univariate Multiple Missing Values-An Advanced Re-sampling Method for Correlated Observations
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Author(s):
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Silvia Sharna* and Mian Adnan and Rahmatullah Imon
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Companies:
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Ball State University and Ball State University and Ball State University
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Keywords:
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Average Log Likelihood Function ;
Combination ;
Dummy Missing Value ;
Likelihood Rate ;
Simple Random Sample
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Abstract:
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Since a missing value resembles not only an unknown data of an unknown probability distribution but also their unknown characteristics, it is better to construct a basket of characteristics based on assumed missing values. The missing technique, as demonstrated by Sharna et al (2016), is a kind of check and balance method for estimating a missing value. In this paper we offer an extended version of the iterative estimation method for more than one missing value. This paper also demonstrates a resampling method for generating 1 or 2 correlated observations from the same distribution from where the original sample is drawn.
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Authors who are presenting talks have a * after their name.
